Emerging Artificial Intelligence Applications in Spatial Transcriptomics Analysis
It provides a comprehensive overview for researchers in genomics and bioinformatics, but is incremental as it summarizes existing work.
This review surveys existing artificial intelligence methods for analyzing spatial transcriptomics data, addressing the need for computational tools to handle its unique challenges.
Spatial transcriptomics (ST) has advanced significantly in the last few years. Such advancement comes with the urgent need for novel computational methods to handle the unique challenges of ST data analysis. Many artificial intelligence (AI) methods have been developed to utilize various machine learning and deep learning techniques for computational ST analysis. This review provides a comprehensive and up-to-date survey of current AI methods for ST analysis.